Multidimensional data analysis of load influencing factors in smart distribution network

2018 1st International Conference on Environment Prevention and Pollution Control Technology

生态环境科学

Pan, Xu^1 ; Wang, Jinli^1 ; Li, Yunshuo^1 ; Xie, Wei^2

Power Distribution Department, China Electric Power Research Institute, Beijing

100192, China^1

State Grid Shanghai Municipal Electric Power Company, Shanghai

200122, China^2

关键词: Advanced applications;    Electrical load;    Historical data;    Load forecasting;    Load temperature;    Multi-dimensional data analysis;    Multiple dimensions;    Smart distribution networks;   

Others  :  https://iopscience.iop.org/article/10.1088/1755-1315/199/5/052015/pdf
DOI  :  10.1088/1755-1315/199/5/052015

学科分类：环境科学（综合）

来源: IOP

【 摘 要 】

With the increasing scale of data in smart distribution network, the information contained in massive historical data is richer, and more valuable information can be mined. Based on the demand of electrical load analysis, the relationship between load and various potential factors in nature or society is analyzed from multiple dimensions such as time, space and meteorology, and then quickly matches the important factors. On the basis of matching the influencing factors, the intensity of association between factors and load is deeply excavated. And a more refined model, such as load-temperature model, is established to analyze the law of historical data change and predict the trend of future change, so as to support the advanced application of load forecasting.